Date of Award

Spring 1-1-2013

Document Type


Degree Name

Doctor of Philosophy (PhD)



First Advisor

Martin Boileau

Second Advisor

Ufuk Devrim Demirel

Third Advisor

Robert McNown

Fourth Advisor

Scott Savage

Fifth Advisor

Roberto Pinheiro


The recent study of Schmitt-Grohè and Uribe (2011) show that aggregate neutral productivity and investment-specific technology are cointegrated. How do the two different sources of technological progress share a common stochastic trend? I review the linkage between the cointegration of sectoral productivities and that of neutral productivity and investment-specific technology. In this paper, the linkage is investigated in two economic frameworks: a closed economy and a small open economy.

The first chapter studies U.S. business cycles by considering cointegrated sectoral productivities and investment-specific technology. Applying Johansen cointegration test to U.S. annual data constructed from the EU KLEMS database, this chapter documents that the productivities of consumption-goods and equipment sectors are cointegrated. It conforms further, using the non-linear cointegration test developed by Kapetanios et al. (2006), that the cointegration is nonlinear. Also, I derive a theoretical proposition that sectoral productivities for consumption-goods and equipment are cointegrated if and only if the aggregate neutral productivity and investment-specific technology are cointegrated. Plus, I consider the non-linear cointegration of sectoral productivities to examine the role of the common stochastic trend of sectoral productivities in explaining the movements of investment-specific technology as well as those of interesting macroeconomic aggregates. For this end, I develop a two-sector dynamic stochastic general equilibrium (DSGE) model, where the non-linear cointegration of sectoral productivities is incorporated as a vector error correction model (VECM) with exponential smooth transition(ESTR) error correction term. Most of structural parameters are estimated via maximum likelihood with all significant external innovations. Simulation results show that the innovations of common stochastic trend of sectoral productivities account for half of consumption's, 79 percent of investment's, and 6 percent of hours' long-run variation.

The second chapter investigates the role of technology-embodied imports and investment-specific technology in the business cycles of a small open economy. This chapter documents that, using the EU KLEMS database, the investment-specific technology of Canada and Korea are substantially affected by foreign innovations. Considering the factors consisting investment-specific technology, I construct a dynamic stochastic general equilibrium (DSGE) model for a small open economy and do maximum likelihood estimation for the structural parameters with the Korean data. The simulation results indicates that the terms of trade shock for consumption goods and the shocks of embodied technology in imports explain a sizeable fraction of macroeconomic variations in the Korean economy along with countercyclical trade balance. It also identifies the significant role of the common trend shocks of sectoral productivities on the Korean business cycles, which is consistent to the findings of Aguiar and Gopinath (2007) arguing that shocks to trend growth are the main sources of fluctuation in emerging economies.